The wisdom of Solomon

A quick post for commentary on the new Solomon et al paper in Science express. We’ll try and get around to discussing this over the weekend, but in the meantime I’ve moved some comments over. There is some commentary on this at DotEarth, and some media reports on the story – some good, some not so good. It seems like a topic that is ripe for confusion, and so here are a few quick clarifications that are worth making.

First of all, this is a paper about internal variability of the climate system in the last decade, not on additional factors that drive climate. Second, this is a discussion about stratospheric water vapour (10 to 15 km above the surface), not water vapour in general. Stratospheric water vapour comes from two sources – the uplift of tropospheric water through the very cold tropical tropopause (both as vapour and as condensate), and the oxidation of methane in the upper stratosphere (CH4+2O2 –> CO2 + 2H2O NB: this is just a schematic, the actual chemical pathways are more complicated). There isn’t very much of it (between 3 and 6 ppmv), and so small changes (~0.5 ppmv) are noticeable.

The decreases seen in this study are in the lower stratosphere and are likely dominated by a change in the flux of water through the tropopause. A change in stratospheric water vapour because of the increase in methane over the industrial period would be a forcing of the climate (and is one of the indirect effects of methane we discussed last year), but a change in the tropopause flux is a response to other factors in the climate system. These might include El Nino/La Nina events, increases in Asian aerosols, or solar impacts on near-tropopause ozone – but this is not addressed in the paper and will take a little more work to figure out.

Update: This last paragraph was probably not as clear as it should be. If the lower stratospheric water vapour (LSWV) is relaxing back to some norm after the 1997/1998 El Nino, then what we are seeing would be internal variability in the system which might have some implications for feedbacks to increasing GHGs, and my estimate of that would be that this would be an amplifying feedback (warmer SSTs leading to more LSWV). If we are seeing changes to the tropopause temperatures as an indirect impact from increased Asian aerosol emissions or solar-driven ozone changes, then this might be better thought of as impacting the efficacy of those forcings rather than implying some sensitivity change.

The study includes an estimate of the effect of the observed stratospheric water decadal decrease by calculating the radiation flux with and without the change, and comparing this to the increase in CO2 forcing over the same period. This implicitly assumes that the change can be regarded as a forcing. However, whether that is an appropriate calculation or not needs some careful consideration. Finally, no-one has yet looked at whether climate models (which have plenty of decadal variability too) have phenomena that resemble these observations that might provide some insight into the causes.

Bob: “I’m actually myself a little confused about the difference between the two (in the interface, not in the real world).”

Because an anomaly is a change from a reference point.

How do you define the reference point? Base.

Now, you need a measure to see how it is different. But an instantaneous value isn’t valid. So you need a period. How do you define the period over which you’re going to average to make a value you can use to gauge the change? The interval.

I.e. your annual anomaly is an interval of one year.

How much has it increased in 30 years? Take a base period around 30 years ago that lasts one year.

Also there’s a difference in that the north pole is water underneath, so warm water can cycle underneath and warm the further reaches of the north pole.

But there’s a honkin’ big landmass over the south pole.

Water doesn’t run uphil, so can’t change the south pole like the north.

A very similar effect also makes the south pole more affected by atmospheric changes as shown by the ozone hole: the continent kept the air above the south pole colder and that means denser and that means air from further north can’t get in and mix. So CFCs stayed there longer and acted longer than they could in the north pole.

The subject of polar amplification sounded interesting to me, too, although I (like BPL) have always assumed that it is mostly about albedo.

So, I read around the subject a little, and found that matters are rather more complicated. Albedo plays an important part, but so does a lot of other factors, particularly ocean heat transport. I skimmed Polar amplification of climate change in coupled models (Holland, Bitz 2003) but mostly what I got from such a trivial reading was “it’s complicated”. If you are interested, I imagine that’s a good starting point.

”This heat is now vibrating slower than light at about 10 trillion oscillations per second. It is now shot off and tries to go and hit Buzz Lightyear in outer space. But woops, it now hits dense greenhouse gas molecules first in our atmosphere which are vibrating at the same frequency as the “heat” and so interacts with them. Incoming light has too fast vibrations to interact with the greenhouse gases and just goes right through them.”

I thank you for the most detailed reply. But I have a couple of questions/clarifications. I thought the two [2] main IR wavelengths that cause the molecules in CO2 to vibrate were 4.26um and 15um and those photons would have a frequency of 70 trillion cycles per second and 20 trillion cycles per second respectively. And of course these two [2] frequencies are only a part of the compliment of photons at varying frequencies that are on the black body radiation curve – the rest pass right through CO2 and do reach Buzz Light Year (assuming they don’t bump into another molecule that happens to absorb their particular wavelength well). But I agree that those two frequencies are more than enough to get the molecules moving and heating (just like even longer wavelength photons get water moving in a microwave oven). You gave a great explanation and I got something from it. thanks.

Richard Ordway also wrote – “Dude, this is rocket science. It’s why people like you should not be telling scientists why global warming is not happening and how humans are not causing it”

I apologize if I have come across as trying to tell scientists they are wrong – I’ve said in posts before you guys have forgotten more than I’ll ever know. I come here to ask questions and I’m sorry I came to the party late but I’m here as long as the host of this site will allow me to be. And I’ll abide by his rules since it is his party and I am only a guest. I have no trouble playing by those rules – I’m just trying to learn and this seems like the best place to do that.

> Bob says: 2 February 2010 at 5:24 PM
> Hank, #236:
Bob, thanks; if you can type in (paste in a picture of) some source/info onto the actual image — that’ll help people who bookmark it or get forwarded links to it, to figure out what it’s about. Explanation, URL, anything.

#240 – Bob, thanks for clarifying my position on that. i’m glad i wasn’t the only one to struggle with that anomaly vs. trend on the GISS site. gavin cleared it up for me by relaying that the base period is meaningless when you choose “trend”.

I will await BPL’s response, at least he is willing to discuss the science. Normally, I would not respond to a post of your type; however, in your case, I suspect you could show some promise, if you redirected your enthusiasm. Sad to say your current response leaves much to be desired…

In the meantime, I suggest you might want to review your approach here. Many of us have a strong interest in the science and do not abide Ad Homs very well. Personally, I will generally consider the source and make allowances. Good Luck in your research… (Oh, BTW, try to get the name correct…)

Ah… so the value represented by the grid square on one of the generated “Trends” maps is in fact representative of the slope of the trend line for the underlying data points (i.e. X years of data) for that square (as opposed to the simple difference between the start and end points).

That makes sense, and would account for the minor variations in the two maps.

Thanks. I should have figured that out for myself. I’ll blame it on a long day spent reading too many different manuals (and sneaking off to read climate science during breaks).

I have no problems with models based on “cause and effect”. Personally I am trying to do research that provides the cause and effect of the models you reference. (Models based on “effect” and parametric adjustment sans well defined “cause” worries me a little.)

It is not unlike the black box experiments of grade school. You have a series of levers or wheels that when moved cause a different wheel or level to move a certain amount or effect. The point is you are to try to replicate the effect without knowing the mechanism which drove the effect.

There are many ways to get an effect out for a given input. However, if you are not replicating the mechanics correctly, when there are several interactive black boxes, you might not get the same result as you would if you had known the mechanical operations.

Hence, your simplicity is welcome; however, I will be more confident in the science as we begin to identify the causes. This is part and parcel of my interest in BPL’s sources. I am curious about the content (“mechanics”) of the “black box” that has driven the conclusion offered.

This is not an attempt to make a judgment or a statement, I am trying to understand how several “descriptions of cause” can co-exist. I am striving to try to match up causes with the recent data. Dr. Holland’s work being only one of the “descriptions of cause”.

The AP Wire Service at one point sent out a typographical error saying 20 feet by end of century, which was widely published in newspapers at the time, and has since been corrected except on rumor sites (of all political and whackadoodle persuasions) where you’ll find the error.

A science paper mentioned that number — as wrong, not attributing it to any source — while discussing the issue.

A U. Colorado press release attributed that number to “some scientists” without naming anyone, and there’s no sign they had any basis for the claim.

expectation that the atmosphere’s relative humidity would remain roughly constant

Yes but your source like many of the others, appears to discuss the troposphere. I wonder if the experts can say whether there is any reason for this expectation to apply to the stratosphere, for which the physics is so different?

The models are based on fundamental physics. When we scale those physics-based processes up into a climate simulation, we see climate. When we look at the mid-scale aspects (but still far more complicated than the basic physics everything is based on) we see all sorts of processes produced by the model that mirrors the real world. These processes aren’t coded into the model – they are results of the model.

This void between the basic physics and the final “big picture” product is where all the interesting stuff happens. When the models reproduce these effects well, then it is a really good validation of the model.

However, the model itself doesn’t always help us understand exactly what is going on. After all, we can see the process going on in the real world, and we don’t really understand it fully there, either.

There are loads of examples of effects like this – polar amplification, obviously. Also ENSO and various circulations and oscillations. Some, the models produce really well. Others, not so well. Understanding why the model does or doesn’t behave like the real world can not only help us improve the models, but also help us understand how these processes work in the real world.

To use your example: the physics in the model produces its own “black boxes”. If the model’s black boxes behave in the same way as the real world black boxes, then we are well on the way to understanding what is inside the box. Climate modelling does not work by trying to code something that behaves like each real world black box. It’s much more subtle than that.

I am not a climate modeller, I’m sure Gavin could explain this better. But then, he already has.

The broad picture behind high latitude amplification is pretty well established. Note that in transient simulations, by “polar amplification” we really mean “arctic amplification.” The South as a whole doesn’t change as fast as the Arctic, at least not until equilibrium. As other people have noted, the changing ratio of ice to land/ocean surface and corresponding surface albedo decline is a big factor. In fact, in model simulations that look at the variation in climate sensitivity over a broad range of forcing (out to an ice-free world for instance) the surface albedo feedback can be the main driver in reduced sensitivity as global temperature rises, while water vapor feedback tends to become stronger.

The way the ice-albedo feedback actually works is not generally well described in secondary sources, which tend to oversimplify the picture to just “less reflected radiation” but a real appreciation for the mechanisms involved comes with understanding the heat fluxes between the atmosphere and ocean on multiple timescales. For instance, Arctic amplification is especially prominent in the cold-season, when there is not much incident solar radiation to speak of. In the summer when there is relatively much more solar radiation, much of the energy goes into melting or evaporation rather than surface temperature amplification. So this shows that the picture is a bit more complicated than just “less reflected sunlight.” As Miller et al. (2007) note:

//”The amplification of high-latitude climate change results from complex positive feedbacks involving exchanges of energy and water mass between the ocean, sea ice, and atmosphere. The positive feedback related to changes in sea-ice albedo is one of the most frequently mentioned, however there are other positive feedbacks that are also important. Among these are feedbacks related to water vapor and clouds. Chen et al. [2003, 2006] demonstrated the importance of correctly representing in climate models the relationships among Arctic cloud and radiative properties. The present paper examines how some of these relationships and feedbacks may change in simulations of future climate.”//

Graversen et al. (discussed at RC some time ago) also brought up the issue of poleward heat transport which is relevant as well. In general though, arctic amplification is one of the most robust features of a warmer climate as we progress into the 21st century. By the way, I’m not entirely sure I agree with BPL’s statement, “There is less water vapor in colder air, so CO2 is proportionally more important the closer you get to the poles” as a reason for polar amplification.

Thanks for the reference, I had reviewed Dr. Schmidt’s explanations about 2 years ago and again his re-visit a year ago when they were again coming under attack.

I guess I must be communicating poorly as I am being unspecific; however, I am less interested in specific models then in the real world/empirical physics (versus laboratory/theoretical). (I’m afraid it’s due to the technician versus scientist in me).

As you suggest many models are Bottom-Up, taking into account the known physical properties of atmospheric chemistry and the energy-matter transportation and distribution. If there is any “tweaking” it usually is along the edges where there is a modicum, of data available.

However, if we look at Top-Down modeling similar to that which is used for weather systems, we have a very different approach. Here in we are looking at large scale measurements and attempting to derive high resolution small scale “gridded” process based primarily on historic patterns along with statistical certainty/probability associations with large scale phenomena.

Looking at the former Bottom-Up type we see what is in essence laboratory principles being drug out into the real world; where as in the later Top-Down type, we see the real world being drug into the laboratory. As we all know weather is not climate; however, thirty years of weather variables is a statistically acceptable sample that can be used to describe climate. Hence, many Climate analysis tools still ascribe to the rules of Top-Down, “effects describes cause” models.

Being a layman and a Top-Down, empirical person I have a tendency to wonder at the quality of the data when trying to “create” data where data does not exist when we are trying to increase the resolution of these types of models. To this end I spend a great deal of my time looking at all of the data entering into the public domain and try to see where the implications of peer reviewed data leads me. (Hence the “black box allusion”, the peer reviewed works provide an insight to the “hidden mechanics”.)

As I suggested prior, most times there are what appears to be conflicting data or processes. When I look past the abstracts and conclusions I see something very different when I apply gross insight to the detailed data. Hence, my curiosity as to Barton’s data sets. I am interested to see the sources of the conclusions he shared. This in no way invalidates anyone’s work or sets me up as any more then anyone else. In this case it is me learning and not being taught what I should learn. I believe we call that critical thinking…

To be more specific, to this end I will relate that the most recent data I have seen suggests that the greatest driver of polar amplification may simply be due to an extended presence (stagnant) of anti-cyclonic systems along the Polar Circle. (Just because the latitude is greater does not suggest that these (Rossby) barometric systems are geographically smaller.) Hence, a “Dry Line” of 400 by 200 miles at say 30 Deg. N would have a great deal lower impact on insolation than a similar “Dry Line” at say 65 Deg. N.

Other then that, I only want to see what the data that drove Barton’s conclusion says that would either validate or invalidate this hypothesis. (The thought is this hypothesis may relate to the formation of PSCs and hence interrelate to Stratospheric water vapor content.)

he models are based on fundamental physics. When we scale those physics-based processes up into a climate simulation, we see climate. When we look at the mid-scale aspects (but still far more complicated than the basic physics everything is based on) we see all sorts of processes produced by the model that mirrors the real world. These processes aren’t coded into the model – they are results of the model.

This void between the basic physics and the final “big picture” product is where all the interesting stuff happens. When the models reproduce these effects well, then it is a really good validation of the model.

However, the model itself doesn’t always help us understand exactly what is going on. After all, we can see the process going on in the real world, and we don’t really understand it fully there, either.

Very well said! I would only add, based on my own experience with models running at much smaller scales than climate models, is that with a model I can ask questions about the why the physics is producing the results they are, by adjusting the initial conditions and seeing what happens. I can determine the importance of the Saharan Air Layer on hurricane development by artificially lowering the relative humidity and increasing the dust loading from the observed conditions and then comparing the runs with and without the dry air and dust loading. If there are significant changes, and there are, then the dry air and dust loading play an important role. Which is why if you looked at my experimental source code and compared it to the base source code you would find that it is littered with segments that are commented out. Hm! Didn’t I see something about that in the news just recently

It does not look like the expected rise for the 21st century could even be 400mm, though I have read that The Netherlands is preparing for a sea level rise of 55-110cm — maybe thinking of the next centuries.

Thanks, I understand albedo is part of the puzzle, for me the question is how the albedo has become an issue. The driver for the condition is unlikely to be related to higher surface temperatures as much as greater surface temperatures are a result of the primary driver.

Where it is clear that some ocean heat content transportation is playing a part along the coast of Greenland, over all the primary driver appears to be related to insolation from what I have seen based on the NCEP NH Analysis at the 250 mb isotach station over the last four years.

Going further the current increase in anti-cyclonic conditions that seem to seasonally park in certain sections of the Polar region seems to have a devastating effect on sea ice.

First I am seeking to understand the how and then I would be advancing on the why. I suspect that much of the warming effect of human emissions may be translating into the apparent change in the weather patterns affecting everything from the NAO to the ENSO to the PDO… My goal is to eventually turn towards the drivers for the change in the barometric waves. I am just not there yet.

266 Hank Roberts, and to RC as a whole, I would love to see updated numbers with regards to sea level rise. When that RC article was posted there was no mention of Antarctic melting, which as far as I understand is losing mass (not to be confused with “sea ice extent”; a common “skeptic” arugment). Mass losses which, again as far as I understand, were not predicted by anyone (except maybe coincidentally Hansen in his “scientific reticence” paper).

270 Leo G: High temps on Venus are caused by CO2. Venus is the example of what we don’t want Earth to be like. Oxygen and nitrogen at the same pressure would not cause those high temps. Venus is the proof that CO2 is bad. On Venus, almost the whole atmosphere is CO2.

His tone in this story is a bit surprising. He calls Energy & Environment “peer reviewed” which is only technically true based on what I’ve read there…

This stolen email he points to makes for sorry reading. This is a conspiracy? Someone harasses you for 17-year old data and you can’t find it? It’s not as if the Chinese data is inconsistent with other studies.

“I read an article last year that the high temps on Venus are from the atmospheric pressure. Wrong?”

Cart before horse, there Leo. Causation is wrong. If you have a lot of CO2 then you have a lot of air. Therefore you have a lot of pressure. Therefore you have higher temps because PV=nRT.

“Wrong” is not the word, but “not right” doesn’t cover it. It’s a bit like the weak anthropic principle saying “this universe is right for human life because if it weren’t we wouldn’t be here to wonder about it” then saying that the presence of humans causes a universe to be able to support human life.

I also suspect that they didn’t actually say what you said. I.e. could have been “high pressures and high temperatures on the surface of Venus…” which you transmogrified by rephrasing into “high temperatures caused by high pressures at the surface of Venus”.

Leo G #270: when you compress a gas, all else being unchanged, it gets warmer. However if you have a planet free to radiate to space, as the gas compresses, any extra heat generated will radiate out. So any heat caused by compression will only be retained on a planetary time scale if it can’t escape. The long-term temperature of a planet depends on on-going energy sources and the rate at which energy radiates out. That means [geothermal energy + solar energy – net outward flux], of which the first term is only enough to get you a little over absolute zero on an earth-like planet. It’s a bit more complicated than that because the atmosphere gets in the way, hence the need for sophisticated computer models, but that captures the essence.

This is essentially the physics of how a refrigerator works. A compressor compresses gas, which heats up, and is allowed to vent out the heat. Then the gas at room temperature is decompressed and cools down.

Venus has been well studied for a long time. If there was an alternative theory I’m sure we’d have heard of it by now. For example:

UN warns of 70 percent desertification by 2025
Published by Jim on Monday, October 5, 2009 at 4:15 PM

BUENOS AIRES (AFP) — Drought could parch close to 70 percent of the planet’s soil by 2025 unless countries implement policies to slow desertification, a senior United Nations official has warned.
“If we cannot find a solution to this problem… in 2025, close to 70 percent could be affected,” Luc Gnacadja, executive secretary of the United Nations Convention to Combat Desertification, said Friday.
Drought currently affects at least 41 percent of the planet and environmental degradation has caused it to spike by 15 to 25 percent since 1990, according to a global climate report.
“There will not be global security without food security” in dry regions, Gnacadja said at the start of the ninth UN conference on the convention in the Argentine capital.

The “runaway greenhouse” applied while Venus still had oceans. Evaporation of water vapor and surface heating fed back on each other until the whole ocean evaporated, and then photodissociation removed the hydrogen and left the oxygen. That’s what brought the runaway to an end. Venus still has a greenhouse effect–the fiercest greenhouse effect in the Solar system–but not a runaway greenhouse effect.

2. The prediction is still about right for the world. If drought went from 12% to 30% 1970-2002, and increases at the same rate in the future, it will be 75% in 2034. Do the math. A factor of 2.5 every 32 years. Maybe it will turn out to be sigmoid and take longer than that. Maybe our warming will kick in geophysical feedbacks that will make the Earth completely uninhabitable (see Mark Lynas’s “Six Degrees”). In any case, my prediction is not alarmist or hysterical or anything else. It’s just an extrapolation based on something we’re already observing.

Yes, completely wrong. Static pressure can’t continue to generate heat; that would make it a perpetual motion machine of the first kind. Even if the Cytherean atmosphere heated up by being compressed, that heat would eventually radiate away. Venus is hot because of the greenhouse effect. If its atmosphere were pure oxygen at the same pressure, it would be frozen over.

JPR #278 (maybe), looks fine to me, but this is my reading of a potted history of the Ozone Hole and connections either made by myself or inspired by others, so feel free to change them if someone who’d studied this comes along and proffers a more accurate position.

Your explanation is not correct. Venus is hot because of the optical properties of the atmosphere, admitting optical light more easily than it releases infrared light. An argon atmosphere, which is pretty transparent at all wavelengths, would be cooler. If it had the same mass, it would have the same surface pressure because that is what is needed to hold it up, but the temperature would be the same as the case with no atmosphere. In order to have that high pressure, the scale height of the atmosphere would be lower and the gas would be denser at the surface.

Paperbagmarlys says: “I might have missed it above but, hey, link, please. Gavin and Co. are way too tolerant of nonsense for my taste but I suspect a blog of deleted comments–real or not–might be amusing.”

I know. I mean entire blogs dedicated to blog comments that were too stupid to be allowed. I mean, isn’t that about the saddest thing you’ve ever read?

L. David Cooke said: “if we look at Top-Down modeling similar to that which is used for weather systems, we have a very different approach.”

My vague understanding is that weather models (at least modern weather models) use roughly the same physics-based approach as climate models. In fact, they have a great deal in common. The main difference is scale, both spatially and temporally. Weather models are run for just a few model days, at very high resolution.

Of course, regional models have to worry about edge effects, and for weather forecasting it is critical that the model be initialised with real world conditions. I suppose in that sense there may be some top-down factors added with the goal of getting more accurate short term forecasts.

But this isn’t really a topic I know much about. Can anyone else comment on the history and present state of weather models, with reference to whether they are top-down or bottom-up? (It doesn’t help that so many weather forecasters keep their models proprietary.)

Limiting ourselves to the “bottom-up” approach of climate models, scope for improvement mostly lies in improving the approximations of first principles physics, molecular mechanics and micro-scale processes. I don’t need to tell you that modelling every atom is impractical…. it’s not like we are seeking the answer to life, the universe and everything.

It is a little simplistic to attribute all drought to climate change. Your general point is right: drought is going to be a major problem in the future. I wouldn’t be so definite about the timescale, though.